R Notebook

library(tidyverse)
library(janitor)
library(lubridate)

deprivation <- read_csv(here::here("raw_data/admissions_by_hb_and_deprivation.csv")) %>% 
  clean_names()

dep_date <- deprivation %>% 
  mutate(
    year = str_extract(week_ending, "^\\d{4}"),
    monthday = str_extract(week_ending, "\\d{4}$"),
    month = str_extract(monthday, "^\\d{2}"),
    day = str_extract(monthday, "\\d{2}$"),
    date = ymd(str_c(year, month, day)), .after = 1
  )

dep_date$simd_quintile <- as_factor(dep_date$simd_quintile)

library(plotly)

ggplotly(dep_date %>%
  group_by(date, simd_quintile) %>% 
  summarise(avg_admissions = mean(number_admissions)) %>% 
  ggplot() +
  aes(x = date, y = avg_admissions, colour = simd_quintile) +
  geom_line())

`summarise()` has grouped output by 'date'. You can override using the `.groups` argument.

```r

input = list(
  
  
)

```